On the Relevance of Volumetric Energy Density in the Investigation of Inconel 718 Laser Powder Bed Fusion

Caiazzo, Fabrizia; Alfieri, Vittorio; Casalino, Giuseppe

doi:10.3390/ma13030538

Cited by 73 publications

(25 citation statements)

References 34 publications

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“…Considerations regarding meltpool geometry [25,26], powder movement [27], and process dynamics [28] that led to the three series of experiments are based on previous work and literature. The intention of series 1 is to identify the effect of standard PBF-LB/M process parameters on the dissolution of high melting particles, while keeping the volumetric energy density (VED, definition given, e.g., in reference [29]) constant. The aim of series 2 was to investigate the effect of an increasing scan speed, while keeping the laser power constant.…”

Section: Methodsmentioning

confidence: 99%

Laser Powder Bed Fusion (PBF-LB/M) Process Strategies for In-Situ Alloy Formation with High-Melting Elements

Huber

Rasch

Schmidt

2021

Metals

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In-situ alloy formation by Laser Powder Bed Fusion (PBF-LB/M) from mixtures of easily available elemental powders is an appealing approach for developing and qualifying new alloys for laser based additive manufacturing of metals. However, especially when dealing with high-melting elements, like W, Ta, Mo, or Nb, it is difficult to achieve a homogeneous element distribution and a complete fusion of the powder particles. The aim of this work was to understand the effects of the PBF-LB/M process parameters (laser power, scan speed, laser spot diameter) and three different single- and double-exposure strategies on the fusion of high-melting W, Ta, Mo, and Nb particles in a Ti-matrix. For this purpose, 220 samples with 10 vol.% of the high-melting particle fraction were prepared and analyzed by optical light microscopy and automated image processing, as well as by scanning electron microscopy (SEM). The results are discussed in the context of current research on the process dynamics of PBF-LB/M. Based on that process strategies to support a complete fusion of high-melting particles during in-situ alloy formation are derived. It is shown that the number of unmolten particles can be at least decreased by a factor of ten compared to the most unfavorable parameter combination. For the lower melting elements, Nb and Mo, a complete fusion without any remaining particles visible in the microsections was achieved for certain parameter combinations. The results prove the feasibility of in-situ alloy formation with high-melting alloying elements, but they also demonstrate the necessity to adjust the PBF-LB/M process strategy to achieve a complete dissolution of the alloying elements.

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Section: Methodsmentioning

confidence: 99%

Laser Powder Bed Fusion (PBF-LB/M) Process Strategies for In-Situ Alloy Formation with High-Melting Elements

Huber

Rasch

Schmidt

2021

Metals

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“…Despite such criticism against the use of VED as design parameter, it continues to be proposed in different works [15,[23][24][25]. In a recent work, Caiazzo et al [26] studied the relevance of VED in the investigation of Inconel 718 LPBF. They proved how different technological and mechanical properties of additively manufacturing parts such as roughness, hardness, number, and size of pores as well as fractional density can be explained in terms of VED that can help the designer in dealing with several process parameters as once.…”

Section: Introductionmentioning

confidence: 99%

A modified volumetric energy density–based approach for porosity assessment in additive manufacturing process design

Ferro

Meneghello

Savio

et al. 2020

Int J Adv Manuf Technol

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Soundness of additively manufactured parts depends on a lot of process and geometrical parameters. A wrong process design leads to defects such as lack of fusion or keyhole porosity that have a detrimental effect on the mechanical properties of the printed parts. Process parameter optimization is thus a formidable challenge that requires in general a huge amount of experimental data. Among the others, heat source power and scan speed are the most defects-affecting parameters to be optimized. The energy density is used in literature to quantify their combination. Unfortunately, in different works it was demonstrated that it fails if used as design parameter mainly because it does not take into account the material properties and the interaction between heat source and the powder bed. In this contribution, a modified volumetric energy density equation that takes into account the powder-heat source interaction to optimize the combination of power-scan speed values for porosity assessment in powder bed fusion process design is proposed and verified on both AlSi10Mg alloy and Maraging steel 300.

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“…However, if the laser power exceeds a certain limit, the increased energy intensity may result in the formation of a high fluctuant keyhole that can introduce additional defects such as subsurface pores or spatters [8]. In addition to increasing surface roughness, the appearance of defects such as pores and lack of fusion can critically reduce the final density of the part [20][21][22].…”

Section: A Process Parameter and Surface Roughnessmentioning

confidence: 99%

Improving Build Quality in Laser Powder Bed Fusion Using High Dynamic Range Imaging and Model-Based Reinforcement Learning

et al. 2021

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In laser-based additive manufacturing (AM) of metal parts from powder bed, information about actual part quality obtained during build is essential for cost-efficient production and high product quality. Reliable and effective monitoring strategies for laser powder bed fusion (LPBF) therefore remain in high demand and are the subject of current research. To address this demand, a novel analysis approach using high dynamic range (HDR) optical imaging in combination with convolutional neural networks (CNN) is proposed for spatially resolved and layer-wise prediction of the surface roughness of LPBF parts. In a further step, the predicted surface roughness maps are used as a feedback signal for a reinforcement learning technique that employs a dynamics model to subsequently identify optimal process parameters under varying and uncertain conditions. The proposed approach ultimately combines the estimation of the local surface roughness based on image texture and model-based reinforcement learning to an in-situ optimization framework for LPBF processes. In addition, the relationship between the layer surface roughness of the part and the overall part density is discussed on the basis of experimental data, which also indicate the applicability of the proposed method in industrial environments. This preliminary study is a first step towards highly adaptive and intelligent machines in the field of automated laser powder bed fusion with the primary goals of reducing production costs and improving the environmental fingerprint as well as print quality.

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On the Relevance of Volumetric Energy Density in the Investigation of Inconel 718 Laser Powder Bed Fusion

Cited by 73 publications

References 34 publications

Laser Powder Bed Fusion (PBF-LB/M) Process Strategies for In-Situ Alloy Formation with High-Melting Elements

Laser Powder Bed Fusion (PBF-LB/M) Process Strategies for In-Situ Alloy Formation with High-Melting Elements

A modified volumetric energy density–based approach for porosity assessment in additive manufacturing process design

Improving Build Quality in Laser Powder Bed Fusion Using High Dynamic Range Imaging and Model-Based Reinforcement Learning

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